Solo Exhibition
Front and Profile
Adam Chin
October 5 - November 1, 2025
About
Front and Profile brings together archival mugshots and machine-generated images to examine the unstable boundary between photographic evidence and machine prediction.
Adam Chin begins with historical booking photographs, using either the frontal or profile view to generate the missing angle through a machine-learning system he modified himself. The resulting image appears photographic, although no camera ever recorded it.
Chin then returns the generated image to the darkroom, pairing it with the archival photograph as a gelatin silver print. The process gives machine prediction the material authority of traditional photography and makes the distinction between record and invention increasingly difficult to hold.
The work also turns toward the systems behind the image. The neural network was trained using a historical mugshot archive whose limitations and racial imbalances become part of what the machine learns. In Front and Profile, technology does not escape history. It absorbs it.
At a moment when facial recognition, surveillance, and generated imagery increasingly shape how people are identified and interpreted, the work asks a more fundamental photographic question: when an image looks like evidence, how much are we willing to believe?
About the Artist
Adam Chin is a San Francisco–based photographer whose practice brings together photography, computer graphics, and questions of representation, perception, and image-making.
Before concentrating more fully on fine-art photography, Chin worked extensively in computer graphics for film and television. He was an early employee of Pacific Data Images, later part of DreamWorks Animation, where his work included computer-graphics lighting for major animated films.
His technical background and photographic practice intersect directly in Front and Profile, where machine learning functions simultaneously as a tool for making images and a subject of inquiry.
Chin holds a BS in Computer Science from Yale University and an MS in Computer Science from Stanford University.